Complicated mining operations and underground mining are important features of China's coal mining. Due to the limitation of cost and time limit, the coal mining operation can usually be completed through cross-op...Complicated mining operations and underground mining are important features of China's coal mining. Due to the limitation of cost and time limit, the coal mining operation can usually be completed through cross-operation construction. Although this method can shorten the working hours to a certain extent, high risks also follow, which puts forward higher requirements for the safety management of underground work. Especially during the period of installation and withdrawal of fully mechanized coal mining face in coal mine, multiple types of work cooperate with each other, auxiliary transportation of explosion-proof vehicles, frame-type trackless rubber-tyred vehicles, battery cars, support vehicles and other vehicles cooperate with each other at the same time. Therefore, reducing the number of potential safety hazards caused by cross-operation has become the top priority of cross-operation safety management. This paper analyzes and summarizes the reasons for the frequent installation and withdrawal of fully mechanized coal mining face and the cooperation of multiple types of work with cross-operation, and formulates corresponding control measures, hoping to help improve the safety management level of coal mine electromechanical transportation and play a role in preventing accidents.展开更多
The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of manufacturing.These technologies enable collecting,storin...The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of manufacturing.These technologies enable collecting,storing,and retrieving essential information from the manufacturing stage.Data collected at sites are shared with others where execution automatedly occurs.The obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing process.However,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major concern.The current research validates the information optimally to offer a minimum set of activities to complete the disassembly process.An optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in manufacturing.However,finding an optimal DSP is complex because of its combinatorial nature.The genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP problem.The converging nature at local optima is a limitation in the traditional GA.This study improvised the GA workability by integrating with the proposed priori crossover operator.An optimality function is defined to reduce disassembly effort by considering directional changes as parameters.The enhanced GA method is tested on a real-time product to evaluate the performance.The obtained results reveal that diversity control depends on the operators employed in the disassembly attributes.The proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the product.The effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.展开更多
The efficient implementation of computational tasks is critical to quantum computations. In quantum circuits, multicontrol unitary operations are important components. Here, we present an extremely efficient and direc...The efficient implementation of computational tasks is critical to quantum computations. In quantum circuits, multicontrol unitary operations are important components. Here, we present an extremely efficient and direct approach to multiple multicontrol unitary operations without decomposition to CNOT and single-photon gates. With the proposed approach, the necessary twophoton operations could be reduced from O(n^3) with the traditional decomposition approach to O(n), which will greatly relax the requirements and make large-scale quantum computation feasible. Moreover, we propose the potential application to the(n-k)-uniform hypergraph state.展开更多
文摘Complicated mining operations and underground mining are important features of China's coal mining. Due to the limitation of cost and time limit, the coal mining operation can usually be completed through cross-operation construction. Although this method can shorten the working hours to a certain extent, high risks also follow, which puts forward higher requirements for the safety management of underground work. Especially during the period of installation and withdrawal of fully mechanized coal mining face in coal mine, multiple types of work cooperate with each other, auxiliary transportation of explosion-proof vehicles, frame-type trackless rubber-tyred vehicles, battery cars, support vehicles and other vehicles cooperate with each other at the same time. Therefore, reducing the number of potential safety hazards caused by cross-operation has become the top priority of cross-operation safety management. This paper analyzes and summarizes the reasons for the frequent installation and withdrawal of fully mechanized coal mining face and the cooperation of multiple types of work with cross-operation, and formulates corresponding control measures, hoping to help improve the safety management level of coal mine electromechanical transportation and play a role in preventing accidents.
基金The authors are grateful to the Raytheon Chair for Systems Engineering for funding.
文摘The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of manufacturing.These technologies enable collecting,storing,and retrieving essential information from the manufacturing stage.Data collected at sites are shared with others where execution automatedly occurs.The obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing process.However,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major concern.The current research validates the information optimally to offer a minimum set of activities to complete the disassembly process.An optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in manufacturing.However,finding an optimal DSP is complex because of its combinatorial nature.The genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP problem.The converging nature at local optima is a limitation in the traditional GA.This study improvised the GA workability by integrating with the proposed priori crossover operator.An optimality function is defined to reduce disassembly effort by considering directional changes as parameters.The enhanced GA method is tested on a real-time product to evaluate the performance.The obtained results reveal that diversity control depends on the operators employed in the disassembly attributes.The proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the product.The effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.
基金supported by the National Natural Science Foundation of China(Grant No.11574093)the Natural Science Foundation of the Fujian Province of China(Grant No.2017J01004)the Promotion Program for Young and Middle-aged Teachers in Science and Technology Research of Huaqiao University(Grant No.ZQN-PY113)
文摘The efficient implementation of computational tasks is critical to quantum computations. In quantum circuits, multicontrol unitary operations are important components. Here, we present an extremely efficient and direct approach to multiple multicontrol unitary operations without decomposition to CNOT and single-photon gates. With the proposed approach, the necessary twophoton operations could be reduced from O(n^3) with the traditional decomposition approach to O(n), which will greatly relax the requirements and make large-scale quantum computation feasible. Moreover, we propose the potential application to the(n-k)-uniform hypergraph state.
